Evidence map›Paper›PMID 41676579›Full record

ArticlebioRxiv : the preprint server for biology2026

A Functional Metabolomics Framework to Track Microbiome Drug Metabolism.

Abzer K Pakkir Shah, Anne Griesshammer, Paolo Stincone, Jarmo-Charles Kalinski, Axel Walter, Mingxun Wang, Lisa Maier, Daniel Petras

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Abzer K Pakkir ShahInterfaculty Institute for Microbiology and Infection Medicine Tübingen, University of Tübingen, Tübingen, Germany.ORCID 0000-0002-5629-8331
Anne GriesshammerInterfaculty Institute for Microbiology and Infection Medicine Tübingen, University of Tübingen, Tübingen, Germany.
Paolo StinconeInterfaculty Institute for Microbiology and Infection Medicine Tübingen, University of Tübingen, Tübingen, Germany.ORCID 0000-0002-2214-6655
Jarmo-Charles KalinskiDepartment of Biochemistry, University of California Riverside, Riverside, CA, USA.ORCID 0000-0001-9641-2912
Axel WalterInterfaculty Institute for Microbiology and Infection Medicine Tübingen, University of Tübingen, Tübingen, Germany.
Mingxun WangDepartment of Computer Science, University of California Riverside, Riverside, CA, USA.ORCID 0000-0001-7647-6097
Lisa MaierInterfaculty Institute for Microbiology and Infection Medicine Tübingen, University of Tübingen, Tübingen, Germany.ORCID 0000-0002-6473-4762
Daniel PetrasInterfaculty Institute for Microbiology and Infection Medicine Tübingen, University of Tübingen, Tübingen, Germany.ORCID 0000-0002-6561-3022

Funding

Collaborative Microbial Metabolite CenterU24DK133658 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PIETER C DORRESTEIN · 2022 to 2026
$2.9M
Understanding the Impact of Xenobiotic Metabolism on the Gut Microbiome and Resilience against Gastrointestinal PathogensR35GM160154 · NIGMS · UNIVERSITY OF CALIFORNIA RIVERSIDE · PI Daniel Petras · 2025 to 2026
$747k
NIDDK NIH HHS U24 DK133658NIGMS NIH HHS R35 GM160154
6 · The paper itself

Abstract

Understanding how gut microbes transform drugs, and how this influences microbiome composition and function, remains a key question to better understand the efficacy and side effects of pharmaceuticals. To accelerate the discovery of microbiome-derived drug metabolites, we developed a functional metabolomics workflow that combines the use of synthetic microbial communities (SynComs) with a time-series resolved molecular networking approach and advanced computational metabolite annotation. We demonstrate how this framework can be used to illuminate chemical transformation dynamics in a gut SynCom (Com20) with 50 clinical drugs. Our results highlight a multitude of drug metabolites, including multi-step metabolic cascades, some of which correlated to shifts in microbial taxa, suggesting functional links between microbiome composition and biochemical transformations. Our computational data analysis workflow is publicly available through the GNPS2 ecosystem at chemprop.gnps2.org, which can be used to prioritize biotransformations and other (bio)chemical reactions in various biological and abiotic systems.

Indexed as

Computational metabolomicsDrug metabolismFunctional metabolomicsGut microbiomeMicrobial biotransformationNon-Targeted metabolomicsTransformation directionality

Identifiers

PMID41676579
PMCPMC12889426

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.